{"title":"Data transfer management policy optimization for unified memory","authors":"Hengliang Guo, Long Zhang, Yi Zhang, Jianan Li","doi":"10.1109/CISCE58541.2023.10142582","DOIUrl":null,"url":null,"abstract":"OpenMP 4.5 refines the offload feature to better support heterogeneous computing. Explicit specification programming is currently required to optimize data transfer in OpenMP offload programs, but manual programming is not efficient or performant. Although DCU-supported unified memory provides a scheme for compilers to implicitly manage data transfers, target offload programs using unified memory perform poorly when program requests exceed the physical memory size. Therefore, this paper proposes a UMAT scheme for automatically optimizing unified memory-based data transfer management, which guides runtime management of data transfers by calculating the access frequency of data objects in the unified memory space. Test results show that the scheme has significant performance improvement for target offload programs using unified memory.","PeriodicalId":145263,"journal":{"name":"2023 5th International Conference on Communications, Information System and Computer Engineering (CISCE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Conference on Communications, Information System and Computer Engineering (CISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISCE58541.2023.10142582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
OpenMP 4.5 refines the offload feature to better support heterogeneous computing. Explicit specification programming is currently required to optimize data transfer in OpenMP offload programs, but manual programming is not efficient or performant. Although DCU-supported unified memory provides a scheme for compilers to implicitly manage data transfers, target offload programs using unified memory perform poorly when program requests exceed the physical memory size. Therefore, this paper proposes a UMAT scheme for automatically optimizing unified memory-based data transfer management, which guides runtime management of data transfers by calculating the access frequency of data objects in the unified memory space. Test results show that the scheme has significant performance improvement for target offload programs using unified memory.